Analysis of the factors affecting the housing prices in neighbourhood scale with hedonic price model: The case of Esenkent neighbourhood

Housings are one of the most important spaces in human life and play a significant role in the construction and real estate sectors. The sale price of a house represents its financial value. Housing prices are influenced by factors such as the physical and location-related characteristics of the property, supply and demand equilibrium, economic growth, interest rates, income levels, demographic changes, and limitations in housing supply. Additionally, housing prices should be considered in terms of the balance of an economy and financial stability. Rapid price increases and radical changes can pose the risk of a housing bubble, which can lead to reasons that affect financial stability. Housing price analysis have critical importance in determining the value of a housing structure and understanding the factors in the housing market by examining the features of the house. These analyses are necessary for determining the correct selling price of a house, facilitating fair housing transactions, and making informed investment decisions. They are also important for tracking market trends and developments in the housing market and gaining knowledge about value increase or decrease in a region. One of the most significant factors affecting the sale price of a house is its location. Factors such as proximity to the city center, business centers, transportation networks, and the social and demographic characteristics of the neighborhood all affect housing prices. The dynamics of housing markets in different regions develop within the framework of these characteristics. Therefore, when conducting price analysis that evaluate factors influencing housing prices, the characteristics of the property should be considered alongside the dynamics of the region where the property is located. Within the scope of this study, factors affecting housing prices were evaluated at the neighborhood scale, and the impact of these factors on housing prices was analyzed in a short timeline to avoid the economic change effect on the analysis. In the analysis conducted in the Esenkent Neighborhood of İstanbul, micro-level factors such as population density, supply and demand balance in the neighborhood, property types, physical conditions, features of existing houses, average age of houses, and demographic characteristics of households were taken into consideration. In this study, numerical and statistical analyses were performed using the Hedonic Price Model method to analyze the factors affecting housing prices. In the Hedonic Price Model, the price of a consumer good is estimated by separating it into its component features, and the sale price of the good is defined as the sum of the prices associated with its features. In the Hedonic Price Model, these feature values are referred to as hedonic prices. While the Hedonic Price Model is used for the analyses of different consumer goods, it is also one of the most commonly used methods in housing price analysis. In the model, the sale price of a house is considered as the sum of the prices of all features and components that make up its heterogeneous structure. These features may include physical attributes such as square footage, number of bedrooms and bathrooms, as well as location factors such as proximity to amenities, transportation options, and neighborhood characteristics. The Hedonic Price Model can be constructed using four different functional forms in which the sale price and feature values are considered in logarithmic and linear forms. The most commonly used functional form in housing price analysis is the semi logarithmic function form, where the sale price of the house is in logarithmic form and the values associated with features are in linear form. The logarithmic-linear function form, which was also employed in this thesis, allows for calculating the percentage impact of a one-unit change in numerical values of housing features or the presence or absence of certain dummy variables on the sale price of houses. In this study, after explaining the concepts related to the housing market and the methodology used, a detailed literature review was conducted, by examining the studies that used the hedonic price model to analyze the factors influencing housing sale prices in different research areas. Along with the variables and methods adopted in these studies, the findings obtained were examined to understand the impact of the characteristics of the study area on the model structure. When determining the variables to be used in the hedonic price model established within the scope of Esenkent Neighbourhood and discussion the findings, the results of the previous studies were taken into account. In the hedonic price model established for the Esenkent Neighborhood, 18 independent variables representing the features of the study area were examined, and the effects of these variables on housing prices were calculated. According to the results of the model, the features related to houses, such as area, number of floors in the building, having a 1+1 layout, building age, the presence of a closed garage, built-in decoration, dressing room, and pool view, were statistically significant and their marginal values on housing sale prices were calculated. The effects of features that can be expressed numerically, such as square footage, number of rooms, floor of the house, number of floors in the building, and age of the building, on housing sale prices were shown on scatterplots and Kernel regression graphs to determine the boundaries within which these features have an impact. Additionally, it was observed that the proximity to schools, hospitals, shopping malls and bus stops within walking distance in the neighborhood had no marginal impact on housing prices. The findings of the model established within the scope of the study, were discussed in conjunction with the characteristics of the study area. Further, comparisons were made between the findings of this study conducted in the neighborhood scale and the findings of other relevant studies to draw conclusions. According to the findings, the hedonic price model established at a deeper level, specifically the neighborhood scale, has proven to be a successful model in explaining the impact of housing characteristics on housing sale prices. However, it is also evident from the study's findings that the factors influencing housing prices at the neighborhood level differ from those of cities and districts. Housing sale prices and the amount of Money that buyers are willing to pay for housing characteristics can be considered as a tangible indicator of the preferences and demands of the residents in that specific study area. In this context, especially in urban regeneration and renewal projects, evaluating housing price analyses at the neighborhood scale is of great importance in order to establish a reliable source of information.